高抗扰高精度无人机着舰纵向飞行控制

刘宪飞; 王勇; 张代兵

doi:10.13700/j.bh.1001-5965.2016.0679

高抗扰高精度无人机着舰纵向飞行控制

doi: 10.13700/j.bh.1001-5965.2016.0679

1.
北京航空航天大学自动化科学与电气工程学院, 北京 100083
2.
国防科技大学机电工程与自动化学院, 长沙 410073

详细信息

作者简介:
刘宪飞男, 硕士研究生; 主要研究方向:飞行控制工程应用

王勇男, 博士, 研究员, 博士生导师; 主要研究方向:先进控制理论及飞行控制工程应用

通讯作者:
王勇, E-mail:wyuav@buaa.edu.cn

中图分类号: V249
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出版历程
- 收稿日期: 2016-08-23
- 录用日期: 2016-11-04
- 网络出版日期: 2017-09-20

High-immunity high-precision longitudinal flight control for UAV's carrier landing

1.
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
2.
School of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, China

More Information

Corresponding author: WANG Yong, E-mail: wyuav@buaa.edu.cn

摘要

摘要:
针对无人机着舰过程中舰尾流扰动和甲板运动扰动对着舰点散布的影响，对复杂着舰环境下的无人机着舰纵向控制策略、控制结构和控制律参数设计方法进行研究。针对常规控制结构抗扰能力不足的问题，提出了无人机着舰纵向多操纵面平衡态直接力控制（DFC）策略及控制结构。提出了面向着舰点散布的控制律参数优化设计方法，该方法在保证系统满足稳定裕度指标的基础上，综合考虑了舰尾流扰动和甲板运动扰动对着舰点散布的影响，使2种扰动造成的着舰点散布最小。构建控制律参数优化设计问题，通过粒子群优化（PSO）算法进行优化设计，得到高抗扰性能的控制律参数。在控制律参数优化中考虑舰尾流和甲板运动的功率谱密度分布，使设计更具有针对性，减小了控制律设计的保守性，进一步提高控制的抗扰性能。算例设计及仿真验证了多操纵面平衡态DFC控制结构在抵抗舰尾流扰动和甲板运动扰动方面的优异性能，并证明了所提控制律参数设计方法的有效性。
- 舰载无人机 /
- 着舰 /
- 直接力控制(DFC) /
- 控制律优化设计 /
- 功率谱密度 /
- 粒子群优化(PSO)
Abstract:
Research on the control strategy, control structure and control law parameter design method is developed in this paper to realize flight control with high-precision performance in the longitude channel of UAV, aimed at solving the impact of sophisticated landing environment, including both the air-wake disturbance and the deck motion disturbance, on touchdown points. First, longitudinal control strategy and structure based on direct force control (DFC) and multi-surface for UAV's carrier landing are proposed on account of insufficient disturbance rejection ability of regular control structure. Second, an approach for designing control law parameters is presented. Control law parameters obtained by this approach which gives priority to the stability margin of the control system, make the position deviation from the ideal touchdown point to be the lowest under the sophisticated landing environment. A problem of optimum design based on this approach is constructed so that control law parameters with high-precision and high-immunity performance could be produced through particle swarm optimization (PSO) algorithm. The power spectrum densities of both the air-wake disturbance and the deck motion disturbance are analyzed to reduce the conservatism of the approach. Finally, the performance of the proposed longitudinal control strategy and structure is illustrated through being compared with the regular one. And the validity of the presented approach is also proved by calculation example and simulation.
- carrier UAV /
- carrier landing /
- direct force control (DFC) /
- control law optimization design /
- power spectrum density /
- particle swarm optimization (PSO)

HTML全文

图 1 ACLS常规纵向控制结构

Figure 1. Regular longitudinal control structure of ACLS

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图 2 多操纵面平衡态DFC控制结构

Figure 2. Control structure based on multi-surface equilibrium-state DFC

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图 3 舰尾流水平分量和垂直分量

Figure 3. Horizontal component and vertical component of air-wake

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图 4 舰尾流水平和垂直分量功率谱密度

Figure 4. Power spectrum density of air-wake horizontal and vertical component

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图 5 甲板运动仿真模型

Figure 5. Simulation model of deck motion

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图 6 理想着舰点高度信号及其功率谱密度

Figure 6. Altitude signal of ideal touchdown point and its power spectrum density

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图 7 控制律优化设计结构示意图

Figure 7. Schematic diagram of control law optimization design structure

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图 8 PSO参数寻优流程图

Figure 8. Flowchart of parameter optimization with PSO

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图 9 适应度变化曲线

Figure 9. Changing curves of fitness

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图 10 不同控制结构对u的抑制能力对比

Figure 10. Comparison of u inhibition ability between different control structures

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图 11 不同控制结构对w的抑制能力对比

Figure 11. Comparison of w inhibition ability between different control structures

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图 12 不同控制结构的舰尾流扰动抑制能力对比

Figure 12. Comparison of inhibition ability of air-wake disturbance between different control structures

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图 13 不同控制结构跟踪甲板运动能力对比

Figure 13. Comparison of ability to track deck motion between different control structures

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图 14 不同控制结构着舰点纵向散布对比

Figure 14. Comparison of longitudinal distribution of touchdown points between different control structures

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表 1 100次着舰仿真纵向散布统计结果

Table 1. Longitudinal deviation statistic results of 100 carrier landing simulations

控制结构类型	着舰偏差均值	着舰偏差均方根	理想着舰次数	允许着舰次数	着舰成功率/ %
DFC	-1.84	3.97	80	100	100
常规	10.04	10.53	30	57	57

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